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A Prospective Study to Evaluate the Diagnostic Accuracy of Computer-aided Diagnosis (CADx) System in Real-time Characterization of Colorectal Neoplasia — CADx  

Colorectal Neoplasms Clinical Trial

Official title:
A Prospective Study to Evaluate the Diagnostic Accuracy of Computer-aided Diagnosis (CADx) System in Real-time Characterization of Colorectal Neoplasia

Clinical Trial Summary

The investigators hypothesize that a newly developed CADx system will have a higher diagnostic accuracy in predicting histopathology of colorectal neoplasia than both expert and junior endoscopists.

Clinical Trial Description

Accurate diagnosis and characterization of colorectal polyps is essential before endoscopic resection. Optical diagnosis by enhanced imaging modality (e.g. Narrow Band Imaging, NBI) allows real-time prediction of histopathology. It can assist endoscopists to select the appropriate technique and differentiate between neoplastic or non-neoplastic polyps. Nevertheless, due to the substantial inter-observer variability, the widespread use was limited. Recently, artificial intelligence and computer-aided polyp diagnosis (CADx) systems have evolved rapidly. The major limitation was the heterogeneity from different types of imaging modalities. Endocytoscopic images require extra steps for pre-staining and magnification, which are time consuming and operator dependent. As a result, it limits the generalisability and applicability in real-world settings. A novel CADx system will be developed for real-time histopathological prediction of colorectal neoplasia, by using non-magnified conventional white-light and image enhanced endoscopy (NBI). The diagnostic accuracy of this CADx system will be compared with both expert and junior endoscopists. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT05414383
Study type Observational
Source Chinese University of Hong Kong
Contact Felix Sia
Phone 26370428
Email felixsia@cuhk.edu.hk
Status Not yet recruiting
Phase
Start date December 2024
Completion date December 31, 2025
View Details
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